Match Selection and Refinement for Highly Accurate Two-View Structure from Motion

Abstract : We present an approach to enhance the accuracy of structure from motion (SfM) in the two-view case. We first answer the question: " fewer data with higher accuracy, or more data with less accuracy? " For this, we establish a relation between SfM errors and a function of the number of matches and their epipolar errors. Using an accuracy estima-tor of individual matches, we then propose a method to select a subset of matches that has a good quality vs. quantity compromise. We also propose a variant of least squares matching to refine match locations based on a focused grid and a multi-scale exploration. Experiments show that both selection and refinement contribute independently to a better accuracy. Their combination reduces errors by a factor of 1.1 to 2.0 for rotation, and 1.6 to 3.8 for translation.
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Communication dans un congrès
Proceedings of ECCV, Sep 2014, Zurich, Switzerland. pp.818-833, 2014, 〈10.1007/978-3-319-10605-2_53〉
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Zhe Liu, Pascal Monasse, Renaud Marlet. Match Selection and Refinement for Highly Accurate Two-View Structure from Motion. Proceedings of ECCV, Sep 2014, Zurich, Switzerland. pp.818-833, 2014, 〈10.1007/978-3-319-10605-2_53〉. 〈hal-01153274〉

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